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data-dom-id="Pill-react-component-2154a0ea-b8fe-4301-a376-35d2ac75ad10"></div> <div id="Pill-react-component-2154a0ea-b8fe-4301-a376-35d2ac75ad10"></div> </a></div></div></div></div><div class="right-panel-container"><div class="user-content-wrapper"><div class="uploads-container" id="social-redesign-work-container"><div class="upload-header"><h2 class="ds2-5-heading-sans-serif-xs">Uploads</h2></div><div class="documents-container backbone-social-profile-documents" style="width: 100%;"><div class="u-taCenter"></div><div class="profile--tab_content_container js-tab-pane tab-pane active" id="all"><div class="profile--tab_heading_container js-section-heading" data-section="Papers" id="Papers"><h3 class="profile--tab_heading_container">Papers by Petter Minnhagen</h3></div><div class="js-work-strip profile--work_container" data-work-id="93603213"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/93603213/Consistency_test_of_the_multiple_meaning_model"><img alt="Research paper thumbnail of Consistency test of the multiple meaning model" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/93603213/Consistency_test_of_the_multiple_meaning_model">Consistency test of the multiple meaning model</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">&lt;p&gt;According to the multiple meaning model the parameter &lt;i&gt;d&lt;/i&gt; (see &lt;a hr...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">&lt;p&gt;According to the multiple meaning model the parameter &lt;i&gt;d&lt;/i&gt; (see &lt;a href=&quot;<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.t002&quot" rel="nofollow">http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.t002&quot</a>; target=&quot;_blank&quot;&gt;Table 2&lt;/a&gt;) should give a sensible approximative estimate of the average number of multiple meanings per character within a text &lt; &lt;i&gt;f&lt;/i&gt; &gt;. The figure shows that &lt; &lt;i&gt;f&lt;/i&gt; &gt; increases with the size of the text &lt;i&gt;M&lt;/i&gt;. This is consistent with the fact the number of uses of a character increases and hence the chance that more of its multiples meanings appears in the text. For the same reason &lt; &lt;i&gt;f&lt;/i&gt; &gt; increases with the average number of uses of a character &lt; &lt;i&gt;k&lt;/i&gt; &gt;. In addition the chance for a larger number of dictionary meanings is larger for a more frequent character (see &lt;a href=&quot;<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.g006&quot" rel="nofollow">http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.g006&quot</a>; target=&quot;_blank&quot;&gt;Fig 6&lt;/a&gt;). The inset shows how &lt; &lt;i&gt;k&lt;/i&gt; &gt; increases with &lt;i&gt;M&lt;/i&gt;.&lt;/p</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="93603213"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="93603213"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 93603213; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=93603213]").text(description); $(".js-view-count[data-work-id=93603213]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 93603213; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='93603213']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 93603213, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=93603213]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":93603213,"title":"Consistency test of the multiple meaning model","translated_title":"","metadata":{"abstract":"\u0026lt;p\u0026gt;According to the multiple meaning model the parameter \u0026lt;i\u0026gt;d\u0026lt;/i\u0026gt; (see \u0026lt;a href=\u0026quot;http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.t002\u0026quot; target=\u0026quot;_blank\u0026quot;\u0026gt;Table 2\u0026lt;/a\u0026gt;) should give a sensible approximative estimate of the average number of multiple meanings per character within a text \u0026lt; \u0026lt;i\u0026gt;f\u0026lt;/i\u0026gt; \u0026gt;. The figure shows that \u0026lt; \u0026lt;i\u0026gt;f\u0026lt;/i\u0026gt; \u0026gt; increases with the size of the text \u0026lt;i\u0026gt;M\u0026lt;/i\u0026gt;. This is consistent with the fact the number of uses of a character increases and hence the chance that more of its multiples meanings appears in the text. For the same reason \u0026lt; \u0026lt;i\u0026gt;f\u0026lt;/i\u0026gt; \u0026gt; increases with the average number of uses of a character \u0026lt; \u0026lt;i\u0026gt;k\u0026lt;/i\u0026gt; \u0026gt;. In addition the chance for a larger number of dictionary meanings is larger for a more frequent character (see \u0026lt;a href=\u0026quot;http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.g006\u0026quot; target=\u0026quot;_blank\u0026quot;\u0026gt;Fig 6\u0026lt;/a\u0026gt;). The inset shows how \u0026lt; \u0026lt;i\u0026gt;k\u0026lt;/i\u0026gt; \u0026gt; increases with \u0026lt;i\u0026gt;M\u0026lt;/i\u0026gt;.\u0026lt;/p","publication_date":{"day":8,"month":5,"year":2015,"errors":{}}},"translated_abstract":"\u0026lt;p\u0026gt;According to the multiple meaning model the parameter \u0026lt;i\u0026gt;d\u0026lt;/i\u0026gt; (see \u0026lt;a href=\u0026quot;http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.t002\u0026quot; target=\u0026quot;_blank\u0026quot;\u0026gt;Table 2\u0026lt;/a\u0026gt;) should give a sensible approximative estimate of the average number of multiple meanings per character within a text \u0026lt; \u0026lt;i\u0026gt;f\u0026lt;/i\u0026gt; \u0026gt;. The figure shows that \u0026lt; \u0026lt;i\u0026gt;f\u0026lt;/i\u0026gt; \u0026gt; increases with the size of the text \u0026lt;i\u0026gt;M\u0026lt;/i\u0026gt;. This is consistent with the fact the number of uses of a character increases and hence the chance that more of its multiples meanings appears in the text. For the same reason \u0026lt; \u0026lt;i\u0026gt;f\u0026lt;/i\u0026gt; \u0026gt; increases with the average number of uses of a character \u0026lt; \u0026lt;i\u0026gt;k\u0026lt;/i\u0026gt; \u0026gt;. In addition the chance for a larger number of dictionary meanings is larger for a more frequent character (see \u0026lt;a href=\u0026quot;http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.g006\u0026quot; target=\u0026quot;_blank\u0026quot;\u0026gt;Fig 6\u0026lt;/a\u0026gt;). The inset shows how \u0026lt; \u0026lt;i\u0026gt;k\u0026lt;/i\u0026gt; \u0026gt; increases with \u0026lt;i\u0026gt;M\u0026lt;/i\u0026gt;.\u0026lt;/p","internal_url":"https://www.academia.edu/93603213/Consistency_test_of_the_multiple_meaning_model","translated_internal_url":"","created_at":"2022-12-24T07:11:26.049-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":35870771,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Consistency_test_of_the_multiple_meaning_model","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":35870771,"first_name":"Petter","middle_initials":null,"last_name":"Minnhagen","page_name":"PetterMinnhagen","domain_name":"umu","created_at":"2015-10-08T06:30:55.611-07:00","display_name":"Petter Minnhagen","url":"https://umu.academia.edu/PetterMinnhagen"},"attachments":[],"research_interests":[{"id":5541,"name":"Plant Biology","url":"https://www.academia.edu/Documents/in/Plant_Biology"},{"id":6021,"name":"Cancer","url":"https://www.academia.edu/Documents/in/Cancer"},{"id":17960,"name":"Infectious Diseases","url":"https://www.academia.edu/Documents/in/Infectious_Diseases"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":265214,"name":"Rgf","url":"https://www.academia.edu/Documents/in/Rgf"},{"id":543930,"name":"Chinese Characters","url":"https://www.academia.edu/Documents/in/Chinese_Characters"},{"id":1037447,"name":"Deviation","url":"https://www.academia.edu/Documents/in/Deviation"}],"urls":[{"id":27386563,"url":"https://figshare.com/articles/Consistency_test_of_the_multiple_meaning_model_/2669068"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="93603212"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/93603212/Test_of_RGF_including_multiple_meaning_constraints"><img alt="Research paper thumbnail of Test of RGF including multiple meaning constraints" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/93603212/Test_of_RGF_including_multiple_meaning_constraints">Test of RGF including multiple meaning constraints</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">&lt;p&gt;The RGF is in each case predicted from the quadruple of state variables (&lt;i&gt;M&lt;/...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">&lt;p&gt;The RGF is in each case predicted from the quadruple of state variables (&lt;i&gt;M&lt;/i&gt;, &lt;i&gt;N&lt;/i&gt;, &lt;i&gt;k&lt;/i&gt;&lt;sub&gt;&lt;i&gt;max&lt;/i&gt;&lt;/sub&gt;, &lt;i&gt;S&lt;/i&gt;). The data is from three novels in Chinese (see &lt;a href=&quot;<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.t002&quot" rel="nofollow">http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.t002&quot</a>; target=&quot;_blank&quot;&gt;Table 2&lt;/a&gt;). The RGF predictions with multiple meaning constraint are given by the dashed curves. The RGF &lt;i&gt;without&lt;/i&gt; the multiple meaning constraint is predicted from the state variable triple (&lt;i&gt;M&lt;/i&gt;, &lt;i&gt;N&lt;/i&gt;, &lt;i&gt;k&lt;/i&gt;&lt;sub&gt;&lt;i&gt;max&lt;/i&gt;&lt;/sub&gt;) and corresponds to the dotted curves. Only when the multiple meaning constraint significantly improves the RGF-prediction can some specific interpretation be associated with it. As seen from the figure the significance increases with increasing length of the novel.&lt;/p</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="93603212"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="93603212"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 93603212; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=93603212]").text(description); $(".js-view-count[data-work-id=93603212]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 93603212; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='93603212']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 93603212, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=93603212]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":93603212,"title":"Test of RGF including multiple meaning constraints","translated_title":"","metadata":{"abstract":"\u0026lt;p\u0026gt;The RGF is in each case predicted from the quadruple of state variables (\u0026lt;i\u0026gt;M\u0026lt;/i\u0026gt;, \u0026lt;i\u0026gt;N\u0026lt;/i\u0026gt;, \u0026lt;i\u0026gt;k\u0026lt;/i\u0026gt;\u0026lt;sub\u0026gt;\u0026lt;i\u0026gt;max\u0026lt;/i\u0026gt;\u0026lt;/sub\u0026gt;, \u0026lt;i\u0026gt;S\u0026lt;/i\u0026gt;). The data is from three novels in Chinese (see \u0026lt;a href=\u0026quot;http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.t002\u0026quot; target=\u0026quot;_blank\u0026quot;\u0026gt;Table 2\u0026lt;/a\u0026gt;). The RGF predictions with multiple meaning constraint are given by the dashed curves. The RGF \u0026lt;i\u0026gt;without\u0026lt;/i\u0026gt; the multiple meaning constraint is predicted from the state variable triple (\u0026lt;i\u0026gt;M\u0026lt;/i\u0026gt;, \u0026lt;i\u0026gt;N\u0026lt;/i\u0026gt;, \u0026lt;i\u0026gt;k\u0026lt;/i\u0026gt;\u0026lt;sub\u0026gt;\u0026lt;i\u0026gt;max\u0026lt;/i\u0026gt;\u0026lt;/sub\u0026gt;) and corresponds to the dotted curves. Only when the multiple meaning constraint significantly improves the RGF-prediction can some specific interpretation be associated with it. As seen from the figure the significance increases with increasing length of the novel.\u0026lt;/p","publication_date":{"day":8,"month":5,"year":2015,"errors":{}}},"translated_abstract":"\u0026lt;p\u0026gt;The RGF is in each case predicted from the quadruple of state variables (\u0026lt;i\u0026gt;M\u0026lt;/i\u0026gt;, \u0026lt;i\u0026gt;N\u0026lt;/i\u0026gt;, \u0026lt;i\u0026gt;k\u0026lt;/i\u0026gt;\u0026lt;sub\u0026gt;\u0026lt;i\u0026gt;max\u0026lt;/i\u0026gt;\u0026lt;/sub\u0026gt;, \u0026lt;i\u0026gt;S\u0026lt;/i\u0026gt;). The data is from three novels in Chinese (see \u0026lt;a href=\u0026quot;http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.t002\u0026quot; target=\u0026quot;_blank\u0026quot;\u0026gt;Table 2\u0026lt;/a\u0026gt;). The RGF predictions with multiple meaning constraint are given by the dashed curves. The RGF \u0026lt;i\u0026gt;without\u0026lt;/i\u0026gt; the multiple meaning constraint is predicted from the state variable triple (\u0026lt;i\u0026gt;M\u0026lt;/i\u0026gt;, \u0026lt;i\u0026gt;N\u0026lt;/i\u0026gt;, \u0026lt;i\u0026gt;k\u0026lt;/i\u0026gt;\u0026lt;sub\u0026gt;\u0026lt;i\u0026gt;max\u0026lt;/i\u0026gt;\u0026lt;/sub\u0026gt;) and corresponds to the dotted curves. Only when the multiple meaning constraint significantly improves the RGF-prediction can some specific interpretation be associated with it. As seen from the figure the significance increases with increasing length of the novel.\u0026lt;/p","internal_url":"https://www.academia.edu/93603212/Test_of_RGF_including_multiple_meaning_constraints","translated_internal_url":"","created_at":"2022-12-24T07:11:25.889-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":35870771,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Test_of_RGF_including_multiple_meaning_constraints","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":35870771,"first_name":"Petter","middle_initials":null,"last_name":"Minnhagen","page_name":"PetterMinnhagen","domain_name":"umu","created_at":"2015-10-08T06:30:55.611-07:00","display_name":"Petter Minnhagen","url":"https://umu.academia.edu/PetterMinnhagen"},"attachments":[],"research_interests":[{"id":5541,"name":"Plant Biology","url":"https://www.academia.edu/Documents/in/Plant_Biology"},{"id":6021,"name":"Cancer","url":"https://www.academia.edu/Documents/in/Cancer"},{"id":17960,"name":"Infectious Diseases","url":"https://www.academia.edu/Documents/in/Infectious_Diseases"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":265214,"name":"Rgf","url":"https://www.academia.edu/Documents/in/Rgf"},{"id":543930,"name":"Chinese Characters","url":"https://www.academia.edu/Documents/in/Chinese_Characters"},{"id":1037447,"name":"Deviation","url":"https://www.academia.edu/Documents/in/Deviation"}],"urls":[{"id":27386562,"url":"https://figshare.com/articles/Test_of_RGF_including_multiple_meaning_constraints_/2669065"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="93603211"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/93603211/Comparison_between_Chinese_texts_in_characters_and_words"><img alt="Research paper thumbnail of Comparison between Chinese texts in characters and words" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/93603211/Comparison_between_Chinese_texts_in_characters_and_words">Comparison between Chinese texts in characters and words</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">&lt;p&gt;(a) Comparison between characters and words for the novel &lt;i&gt;A Q Zheng Zhuan&lt;/i...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">&lt;p&gt;(a) Comparison between characters and words for the novel &lt;i&gt;A Q Zheng Zhuan&lt;/i&gt; by Xun Lu together with the respective RGF-predictions. (b) The same comparison for the novel &lt;i&gt;Ping Fan De Shi Jie&lt;/i&gt; by Yao Lu. Filled dots correspond to the binned data for Chinese characters and filled triangles the data for words. Full and dashed curves correspond to the respective RGF-predictions and dotted straight lines are the Zipf’s law expectations for the word-frequency distribution. The respective “state”-variables (&lt;i&gt;M&lt;/i&gt;, &lt;i&gt;N&lt;/i&gt;, &lt;i&gt;k&lt;/i&gt;&lt;sub&gt;&lt;i&gt;max&lt;/i&gt;&lt;/sub&gt;) and the corresponding RGF-predictions are given in &lt;a href=&quot;<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.t001&quot" rel="nofollow">http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.t001&quot</a>; target=&quot;_blank&quot;&gt;Table 1&lt;/a&gt;. Note that the translation between words and characters is a deterministic process. Yet the “state”-variables (&lt;i&gt;M&lt;/i&gt;, &lt;i&gt;N&lt;/i&gt;, &lt;i&gt;k&lt;/i&gt;&lt;sub&gt;&lt;i&gt;max&lt;/i&gt;&lt;/sub&gt;) suffice to predict the change in frequency distribution caused by the translation between words and characters.&lt;/p</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="93603211"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="93603211"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 93603211; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=93603211]").text(description); $(".js-view-count[data-work-id=93603211]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 93603211; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='93603211']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 93603211, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=93603211]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":93603211,"title":"Comparison between Chinese texts in characters and words","translated_title":"","metadata":{"abstract":"\u0026lt;p\u0026gt;(a) Comparison between characters and words for the novel \u0026lt;i\u0026gt;A Q Zheng Zhuan\u0026lt;/i\u0026gt; by Xun Lu together with the respective RGF-predictions. (b) The same comparison for the novel \u0026lt;i\u0026gt;Ping Fan De Shi Jie\u0026lt;/i\u0026gt; by Yao Lu. Filled dots correspond to the binned data for Chinese characters and filled triangles the data for words. Full and dashed curves correspond to the respective RGF-predictions and dotted straight lines are the Zipf’s law expectations for the word-frequency distribution. The respective “state”-variables (\u0026lt;i\u0026gt;M\u0026lt;/i\u0026gt;, \u0026lt;i\u0026gt;N\u0026lt;/i\u0026gt;, \u0026lt;i\u0026gt;k\u0026lt;/i\u0026gt;\u0026lt;sub\u0026gt;\u0026lt;i\u0026gt;max\u0026lt;/i\u0026gt;\u0026lt;/sub\u0026gt;) and the corresponding RGF-predictions are given in \u0026lt;a href=\u0026quot;http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.t001\u0026quot; target=\u0026quot;_blank\u0026quot;\u0026gt;Table 1\u0026lt;/a\u0026gt;. Note that the translation between words and characters is a deterministic process. Yet the “state”-variables (\u0026lt;i\u0026gt;M\u0026lt;/i\u0026gt;, \u0026lt;i\u0026gt;N\u0026lt;/i\u0026gt;, \u0026lt;i\u0026gt;k\u0026lt;/i\u0026gt;\u0026lt;sub\u0026gt;\u0026lt;i\u0026gt;max\u0026lt;/i\u0026gt;\u0026lt;/sub\u0026gt;) suffice to predict the change in frequency distribution caused by the translation between words and characters.\u0026lt;/p","publication_date":{"day":8,"month":5,"year":2015,"errors":{}}},"translated_abstract":"\u0026lt;p\u0026gt;(a) Comparison between characters and words for the novel \u0026lt;i\u0026gt;A Q Zheng Zhuan\u0026lt;/i\u0026gt; by Xun Lu together with the respective RGF-predictions. (b) The same comparison for the novel \u0026lt;i\u0026gt;Ping Fan De Shi Jie\u0026lt;/i\u0026gt; by Yao Lu. Filled dots correspond to the binned data for Chinese characters and filled triangles the data for words. Full and dashed curves correspond to the respective RGF-predictions and dotted straight lines are the Zipf’s law expectations for the word-frequency distribution. The respective “state”-variables (\u0026lt;i\u0026gt;M\u0026lt;/i\u0026gt;, \u0026lt;i\u0026gt;N\u0026lt;/i\u0026gt;, \u0026lt;i\u0026gt;k\u0026lt;/i\u0026gt;\u0026lt;sub\u0026gt;\u0026lt;i\u0026gt;max\u0026lt;/i\u0026gt;\u0026lt;/sub\u0026gt;) and the corresponding RGF-predictions are given in \u0026lt;a href=\u0026quot;http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.t001\u0026quot; target=\u0026quot;_blank\u0026quot;\u0026gt;Table 1\u0026lt;/a\u0026gt;. Note that the translation between words and characters is a deterministic process. Yet the “state”-variables (\u0026lt;i\u0026gt;M\u0026lt;/i\u0026gt;, \u0026lt;i\u0026gt;N\u0026lt;/i\u0026gt;, \u0026lt;i\u0026gt;k\u0026lt;/i\u0026gt;\u0026lt;sub\u0026gt;\u0026lt;i\u0026gt;max\u0026lt;/i\u0026gt;\u0026lt;/sub\u0026gt;) suffice to predict the change in frequency distribution caused by the translation between words and characters.\u0026lt;/p","internal_url":"https://www.academia.edu/93603211/Comparison_between_Chinese_texts_in_characters_and_words","translated_internal_url":"","created_at":"2022-12-24T07:11:25.718-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":35870771,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Comparison_between_Chinese_texts_in_characters_and_words","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":35870771,"first_name":"Petter","middle_initials":null,"last_name":"Minnhagen","page_name":"PetterMinnhagen","domain_name":"umu","created_at":"2015-10-08T06:30:55.611-07:00","display_name":"Petter Minnhagen","url":"https://umu.academia.edu/PetterMinnhagen"},"attachments":[],"research_interests":[{"id":5541,"name":"Plant Biology","url":"https://www.academia.edu/Documents/in/Plant_Biology"},{"id":6021,"name":"Cancer","url":"https://www.academia.edu/Documents/in/Cancer"},{"id":17960,"name":"Infectious Diseases","url":"https://www.academia.edu/Documents/in/Infectious_Diseases"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":265214,"name":"Rgf","url":"https://www.academia.edu/Documents/in/Rgf"},{"id":543930,"name":"Chinese Characters","url":"https://www.academia.edu/Documents/in/Chinese_Characters"},{"id":1037447,"name":"Deviation","url":"https://www.academia.edu/Documents/in/Deviation"}],"urls":[{"id":27386561,"url":"https://figshare.com/articles/Comparison_between_Chinese_texts_in_characters_and_words_/2668996"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="93603210"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/93603210/Size_dependence_of_novels_written_in_Chinese_characters"><img alt="Research paper thumbnail of Size dependence of novels written in Chinese characters" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/93603210/Size_dependence_of_novels_written_in_Chinese_characters">Size dependence of novels written in Chinese characters</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">&lt;p&gt;The same two novels as in &lt;a href=&quot;http://www.plosone.org/article/info:doi/10.13...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">&lt;p&gt;The same two novels as in &lt;a href=&quot;<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.g002&quot" rel="nofollow">http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.g002&quot</a>; target=&quot;_blank&quot;&gt;Fig 2&lt;/a&gt; are divided into parts. The frequency distribution of a full novel is compared to the one of a part. (a) &lt;i&gt;P&lt;/i&gt;(&lt;i&gt;k&lt;/i&gt;) for &lt;i&gt;A Q Zheng Zhuan&lt;/i&gt; (filled dots) is compared to the distribution for a typical 10&lt;sup&gt;&lt;i&gt;th&lt;/i&gt;&lt;/sup&gt;-part (filled triangles). Here the word &lt;i&gt;typical&lt;/i&gt; means an average distribution obtained by taking many different 10&lt;sup&gt;&lt;i&gt;th&lt;/i&gt;&lt;/sup&gt; with different starting points. These two functions have quite different shapes. However, the shapes of both are equally well predicted by RGF (curves with dashed and full lines). (b) The distribution of the 10&lt;sup&gt;&lt;i&gt;th&lt;/i&gt;&lt;/sup&gt;-part, which can to very good approximation be trivially obtained from the full book by just &lt;i&gt;randomly&lt;/i&gt; removing 90% of the words from the full book. This corresponds to the dashed curve which is almost identical to the RGF-prediction and both correspond very well to the data. (c-d) The same features for the novel &lt;i&gt;Ping Fan De Shi Jie&lt;/i&gt;. Note that the 10&lt;sup&gt;&lt;i&gt;th&lt;/i&gt;&lt;/sup&gt;-part agrees better with RGF than the full novel.&lt;/p</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="93603210"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="93603210"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 93603210; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=93603210]").text(description); $(".js-view-count[data-work-id=93603210]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 93603210; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='93603210']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 93603210, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=93603210]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":93603210,"title":"Size dependence of novels written in Chinese characters","translated_title":"","metadata":{"abstract":"\u0026lt;p\u0026gt;The same two novels as in \u0026lt;a href=\u0026quot;http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.g002\u0026quot; target=\u0026quot;_blank\u0026quot;\u0026gt;Fig 2\u0026lt;/a\u0026gt; are divided into parts. The frequency distribution of a full novel is compared to the one of a part. (a) \u0026lt;i\u0026gt;P\u0026lt;/i\u0026gt;(\u0026lt;i\u0026gt;k\u0026lt;/i\u0026gt;) for \u0026lt;i\u0026gt;A Q Zheng Zhuan\u0026lt;/i\u0026gt; (filled dots) is compared to the distribution for a typical 10\u0026lt;sup\u0026gt;\u0026lt;i\u0026gt;th\u0026lt;/i\u0026gt;\u0026lt;/sup\u0026gt;-part (filled triangles). Here the word \u0026lt;i\u0026gt;typical\u0026lt;/i\u0026gt; means an average distribution obtained by taking many different 10\u0026lt;sup\u0026gt;\u0026lt;i\u0026gt;th\u0026lt;/i\u0026gt;\u0026lt;/sup\u0026gt; with different starting points. These two functions have quite different shapes. However, the shapes of both are equally well predicted by RGF (curves with dashed and full lines). (b) The distribution of the 10\u0026lt;sup\u0026gt;\u0026lt;i\u0026gt;th\u0026lt;/i\u0026gt;\u0026lt;/sup\u0026gt;-part, which can to very good approximation be trivially obtained from the full book by just \u0026lt;i\u0026gt;randomly\u0026lt;/i\u0026gt; removing 90% of the words from the full book. This corresponds to the dashed curve which is almost identical to the RGF-prediction and both correspond very well to the data. (c-d) The same features for the novel \u0026lt;i\u0026gt;Ping Fan De Shi Jie\u0026lt;/i\u0026gt;. Note that the 10\u0026lt;sup\u0026gt;\u0026lt;i\u0026gt;th\u0026lt;/i\u0026gt;\u0026lt;/sup\u0026gt;-part agrees better with RGF than the full novel.\u0026lt;/p","publication_date":{"day":8,"month":5,"year":2015,"errors":{}}},"translated_abstract":"\u0026lt;p\u0026gt;The same two novels as in \u0026lt;a href=\u0026quot;http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.g002\u0026quot; target=\u0026quot;_blank\u0026quot;\u0026gt;Fig 2\u0026lt;/a\u0026gt; are divided into parts. The frequency distribution of a full novel is compared to the one of a part. (a) \u0026lt;i\u0026gt;P\u0026lt;/i\u0026gt;(\u0026lt;i\u0026gt;k\u0026lt;/i\u0026gt;) for \u0026lt;i\u0026gt;A Q Zheng Zhuan\u0026lt;/i\u0026gt; (filled dots) is compared to the distribution for a typical 10\u0026lt;sup\u0026gt;\u0026lt;i\u0026gt;th\u0026lt;/i\u0026gt;\u0026lt;/sup\u0026gt;-part (filled triangles). Here the word \u0026lt;i\u0026gt;typical\u0026lt;/i\u0026gt; means an average distribution obtained by taking many different 10\u0026lt;sup\u0026gt;\u0026lt;i\u0026gt;th\u0026lt;/i\u0026gt;\u0026lt;/sup\u0026gt; with different starting points. These two functions have quite different shapes. However, the shapes of both are equally well predicted by RGF (curves with dashed and full lines). (b) The distribution of the 10\u0026lt;sup\u0026gt;\u0026lt;i\u0026gt;th\u0026lt;/i\u0026gt;\u0026lt;/sup\u0026gt;-part, which can to very good approximation be trivially obtained from the full book by just \u0026lt;i\u0026gt;randomly\u0026lt;/i\u0026gt; removing 90% of the words from the full book. This corresponds to the dashed curve which is almost identical to the RGF-prediction and both correspond very well to the data. (c-d) The same features for the novel \u0026lt;i\u0026gt;Ping Fan De Shi Jie\u0026lt;/i\u0026gt;. Note that the 10\u0026lt;sup\u0026gt;\u0026lt;i\u0026gt;th\u0026lt;/i\u0026gt;\u0026lt;/sup\u0026gt;-part agrees better with RGF than the full novel.\u0026lt;/p","internal_url":"https://www.academia.edu/93603210/Size_dependence_of_novels_written_in_Chinese_characters","translated_internal_url":"","created_at":"2022-12-24T07:11:25.536-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":35870771,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Size_dependence_of_novels_written_in_Chinese_characters","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":35870771,"first_name":"Petter","middle_initials":null,"last_name":"Minnhagen","page_name":"PetterMinnhagen","domain_name":"umu","created_at":"2015-10-08T06:30:55.611-07:00","display_name":"Petter Minnhagen","url":"https://umu.academia.edu/PetterMinnhagen"},"attachments":[],"research_interests":[{"id":5541,"name":"Plant Biology","url":"https://www.academia.edu/Documents/in/Plant_Biology"},{"id":6021,"name":"Cancer","url":"https://www.academia.edu/Documents/in/Cancer"},{"id":17960,"name":"Infectious Diseases","url":"https://www.academia.edu/Documents/in/Infectious_Diseases"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":265214,"name":"Rgf","url":"https://www.academia.edu/Documents/in/Rgf"},{"id":543930,"name":"Chinese Characters","url":"https://www.academia.edu/Documents/in/Chinese_Characters"},{"id":1037447,"name":"Deviation","url":"https://www.academia.edu/Documents/in/Deviation"}],"urls":[{"id":27386560,"url":"https://figshare.com/articles/Size_dependence_of_novels_written_in_Chinese_characters_/2669032"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="93603209"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/93603209/Nonuniversal_Jumps_and_the_Kosterlitz_Thouless_Transition"><img alt="Research paper thumbnail of Nonuniversal Jumps and the Kosterlitz-Thouless Transition" class="work-thumbnail" src="https://attachments.academia-assets.com/96296030/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/93603209/Nonuniversal_Jumps_and_the_Kosterlitz_Thouless_Transition">Nonuniversal Jumps and the Kosterlitz-Thouless Transition</a></div><div class="wp-workCard_item"><span>Physical Review Letters</span><span>, 1985</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="47f7b4982b306469c2779de4720f2f5d" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":96296030,"asset_id":93603209,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/96296030/download_file?st=MTczMzAxNzgxNyw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="93603209"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="93603209"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 93603209; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=93603209]").text(description); $(".js-view-count[data-work-id=93603209]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 93603209; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='93603209']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 93603209, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "47f7b4982b306469c2779de4720f2f5d" } } $('.js-work-strip[data-work-id=93603209]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":93603209,"title":"Nonuniversal Jumps and the Kosterlitz-Thouless Transition","translated_title":"","metadata":{"publisher":"American Physical Society (APS)","grobid_abstract":"A new set of renormalization equations for the two-dimensional Coulomb gas is derived. Within this new description, the prediction of a universal jump or the prediction that the exponent q is 4 at the critical line breaks down below a certain temperature. Consequently it should be possible to have a Kosterlitz-Thouless transition without a universal jump. A realization is suggested.","publication_date":{"day":null,"month":null,"year":1985,"errors":{}},"publication_name":"Physical Review Letters","grobid_abstract_attachment_id":96296030},"translated_abstract":null,"internal_url":"https://www.academia.edu/93603209/Nonuniversal_Jumps_and_the_Kosterlitz_Thouless_Transition","translated_internal_url":"","created_at":"2022-12-24T07:11:25.358-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":35870771,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":96296030,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/96296030/thumbnails/1.jpg","file_name":"fulltext.pdf","download_url":"https://www.academia.edu/attachments/96296030/download_file?st=MTczMzAxNzgxNyw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Nonuniversal_Jumps_and_the_Kosterlitz_Th.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/96296030/fulltext-libre.pdf?1671897481=\u0026response-content-disposition=attachment%3B+filename%3DNonuniversal_Jumps_and_the_Kosterlitz_Th.pdf\u0026Expires=1733021417\u0026Signature=XDGITV~X3ZHGg8KJrz6MGRdDMHH1rdJLlHU-JnZXvEYOQ8v2UsILhtYXU90nG0cNffU0rIg8t8MWgvskwcUrVij7ALvjO6UiqBxT2ES4eYVh80Q~vmTvnZ~3noJMTmZRTO6IoE3wz7MRCL2scUOyhMQgWDRGNGi74r-iij9ZDrd-4K2B256Y2x81qVuJEhaIe3w8I7X6FKA8N6BM3oDwG-GkCgUGLOk1d0DBRPe1Y-rLnSdHOhQFL3uhrVviSSDBMxIVeT79jwR~PmKLdufwtYJvoHPEei25I7qYHymR72U4a~RwwxTULxdWnRiSCY54Eo9sfrr5fDAiCl8pAnr42w__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Nonuniversal_Jumps_and_the_Kosterlitz_Thouless_Transition","translated_slug":"","page_count":4,"language":"en","content_type":"Work","owner":{"id":35870771,"first_name":"Petter","middle_initials":null,"last_name":"Minnhagen","page_name":"PetterMinnhagen","domain_name":"umu","created_at":"2015-10-08T06:30:55.611-07:00","display_name":"Petter Minnhagen","url":"https://umu.academia.edu/PetterMinnhagen"},"attachments":[{"id":96296030,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/96296030/thumbnails/1.jpg","file_name":"fulltext.pdf","download_url":"https://www.academia.edu/attachments/96296030/download_file?st=MTczMzAxNzgxNyw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Nonuniversal_Jumps_and_the_Kosterlitz_Th.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/96296030/fulltext-libre.pdf?1671897481=\u0026response-content-disposition=attachment%3B+filename%3DNonuniversal_Jumps_and_the_Kosterlitz_Th.pdf\u0026Expires=1733021417\u0026Signature=XDGITV~X3ZHGg8KJrz6MGRdDMHH1rdJLlHU-JnZXvEYOQ8v2UsILhtYXU90nG0cNffU0rIg8t8MWgvskwcUrVij7ALvjO6UiqBxT2ES4eYVh80Q~vmTvnZ~3noJMTmZRTO6IoE3wz7MRCL2scUOyhMQgWDRGNGi74r-iij9ZDrd-4K2B256Y2x81qVuJEhaIe3w8I7X6FKA8N6BM3oDwG-GkCgUGLOk1d0DBRPe1Y-rLnSdHOhQFL3uhrVviSSDBMxIVeT79jwR~PmKLdufwtYJvoHPEei25I7qYHymR72U4a~RwwxTULxdWnRiSCY54Eo9sfrr5fDAiCl8pAnr42w__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[{"id":498,"name":"Physics","url":"https://www.academia.edu/Documents/in/Physics"},{"id":16460,"name":"Statistical Physics","url":"https://www.academia.edu/Documents/in/Statistical_Physics"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":118582,"name":"Physical sciences","url":"https://www.academia.edu/Documents/in/Physical_sciences"},{"id":201464,"name":"Renormalization","url":"https://www.academia.edu/Documents/in/Renormalization"},{"id":288502,"name":"Jump","url":"https://www.academia.edu/Documents/in/Jump"},{"id":288867,"name":"Coulomb","url":"https://www.academia.edu/Documents/in/Coulomb"}],"urls":[{"id":27386559,"url":"http://link.aps.org/article/10.1103/PhysRevLett.54.2351"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="93603154"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/93603154/New_renormalization_equations_for_the_Kosterlitz_Thouless_transition"><img alt="Research paper thumbnail of New renormalization equations for the Kosterlitz-Thouless transition" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/93603154/New_renormalization_equations_for_the_Kosterlitz_Thouless_transition">New renormalization equations for the Kosterlitz-Thouless transition</a></div><div class="wp-workCard_item"><span>Physical Review B</span><span>, 1985</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">A new set of renormalization equations for the two-dimensional Coulomb gas is derived and solved ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">A new set of renormalization equations for the two-dimensional Coulomb gas is derived and solved numerically. These equations give a new picture of the Kosterlitz-Thouless transition. A new temperature T* is found. Above T* the value of the dielectric constant at the transition is εc=1/(4Tc) as before whereas below T* the new result εc&amp;amp;amp;amp;amp;amp;lt;1/(4Tc) is obtained. The singular behavior at</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="93603154"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="93603154"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 93603154; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=93603154]").text(description); $(".js-view-count[data-work-id=93603154]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 93603154; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='93603154']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 93603154, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=93603154]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":93603154,"title":"New renormalization equations for the Kosterlitz-Thouless transition","translated_title":"","metadata":{"abstract":"A new set of renormalization equations for the two-dimensional Coulomb gas is derived and solved numerically. These equations give a new picture of the Kosterlitz-Thouless transition. A new temperature T* is found. Above T* the value of the dielectric constant at the transition is εc=1/(4Tc) as before whereas below T* the new result εc\u0026amp;amp;amp;amp;amp;amp;lt;1/(4Tc) is obtained. The singular behavior at","publisher":"American Physical Society (APS)","publication_date":{"day":null,"month":null,"year":1985,"errors":{}},"publication_name":"Physical Review B"},"translated_abstract":"A new set of renormalization equations for the two-dimensional Coulomb gas is derived and solved numerically. These equations give a new picture of the Kosterlitz-Thouless transition. A new temperature T* is found. Above T* the value of the dielectric constant at the transition is εc=1/(4Tc) as before whereas below T* the new result εc\u0026amp;amp;amp;amp;amp;amp;lt;1/(4Tc) is obtained. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="85183365"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/85183365/Correlations_in_Networks_Associated_to_Preferential_Growth"><img alt="Research paper thumbnail of Correlations in Networks Associated to Preferential Growth" class="work-thumbnail" src="https://attachments.academia-assets.com/89961011/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/85183365/Correlations_in_Networks_Associated_to_Preferential_Growth">Correlations in Networks Associated to Preferential Growth</a></div><div class="wp-workCard_item"><span>Physica Scripta</span><span>, 2005</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="356ffd494feea55aa26060ecd88c5a7d" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":89961011,"asset_id":85183365,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/89961011/download_file?st=MTczMzAxNzgxNyw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="85183365"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="85183365"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 85183365; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="75678809"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/75678809/Exact_numerical_solutions_of_a_nozieres_de_dominicis_type_model_problem"><img alt="Research paper thumbnail of Exact numerical solutions of a nozieres-de dominicis-type model problem" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/75678809/Exact_numerical_solutions_of_a_nozieres_de_dominicis_type_model_problem">Exact numerical solutions of a nozieres-de dominicis-type model problem</a></div><div class="wp-workCard_item"><span>Physics Letters A</span><span>, 1976</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">We infer from a model calculation that, to a very good approximation, the XPS spectra from core e...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">We infer from a model calculation that, to a very good approximation, the XPS spectra from core electrons in simple metals should follow the edge power law up to the first plasmon satellite. The power law indices obtained are in good agreement with recent experimental XPS values for Na, Mg and Al.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="75678809"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75678809"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75678809; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75678809]").text(description); $(".js-view-count[data-work-id=75678809]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75678809; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75678809']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 75678809, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=75678809]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75678809,"title":"Exact numerical solutions of a nozieres-de dominicis-type model problem","translated_title":"","metadata":{"abstract":"We infer from a model calculation that, to a very good approximation, the XPS spectra from core electrons in simple metals should follow the edge power law up to the first plasmon satellite. 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We investigate the phase diagram in the plane of the temperature T and the disorder strength r, and infer, in contrast to a prevailing conclusion in many earlier studies, that the system is superconducting at any disorder strength r for sufficiently low T. It is also argued that the superconducting to normal transition has different nature at weak disorder and strong disorder: termed Kosterlitz-Thouless (KT) type and non-KT type, respectively. The results are compared to earlier works.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="54a26c453852e2aa17e3feea2627827c" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":81279599,"asset_id":72296061,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/81279599/download_file?st=MTczMzAxNzgxOCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="72296061"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="72296061"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 72296061; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=72296061]").text(description); $(".js-view-count[data-work-id=72296061]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 72296061; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='72296061']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 72296061, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "54a26c453852e2aa17e3feea2627827c" } } $('.js-work-strip[data-work-id=72296061]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":72296061,"title":"Phase Transitions in the Two-Dimensional Random Gauge XY Model","translated_title":"","metadata":{"abstract":"The two-dimensional random gauge model, where the quenched random variables are magnetic bond angles uniformly distributed within [-rπ, rπ] (0 ≤ r ≤ 1), is studied via Monte Carlo simulations. We investigate the phase diagram in the plane of the temperature T and the disorder strength r, and infer, in contrast to a prevailing conclusion in many earlier studies, that the system is superconducting at any disorder strength r for sufficiently low T. It is also argued that the superconducting to normal transition has different nature at weak disorder and strong disorder: termed Kosterlitz-Thouless (KT) type and non-KT type, respectively. The results are compared to earlier works.","publication_date":{"day":16,"month":1,"year":2003,"errors":{}}},"translated_abstract":"The two-dimensional random gauge model, where the quenched random variables are magnetic bond angles uniformly distributed within [-rπ, rπ] (0 ≤ r ≤ 1), is studied via Monte Carlo simulations. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> </div><div class="profile--tab_content_container js-tab-pane tab-pane" data-section-id="3705611" id="papers"><div class="js-work-strip profile--work_container" data-work-id="93603213"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/93603213/Consistency_test_of_the_multiple_meaning_model"><img alt="Research paper thumbnail of Consistency test of the multiple meaning model" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/93603213/Consistency_test_of_the_multiple_meaning_model">Consistency test of the multiple meaning model</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">&lt;p&gt;According to the multiple meaning model the parameter &lt;i&gt;d&lt;/i&gt; (see &lt;a hr...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">&lt;p&gt;According to the multiple meaning model the parameter &lt;i&gt;d&lt;/i&gt; (see &lt;a href=&quot;<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.t002&quot" rel="nofollow">http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.t002&quot</a>; target=&quot;_blank&quot;&gt;Table 2&lt;/a&gt;) should give a sensible approximative estimate of the average number of multiple meanings per character within a text &lt; &lt;i&gt;f&lt;/i&gt; &gt;. The figure shows that &lt; &lt;i&gt;f&lt;/i&gt; &gt; increases with the size of the text &lt;i&gt;M&lt;/i&gt;. This is consistent with the fact the number of uses of a character increases and hence the chance that more of its multiples meanings appears in the text. For the same reason &lt; &lt;i&gt;f&lt;/i&gt; &gt; increases with the average number of uses of a character &lt; &lt;i&gt;k&lt;/i&gt; &gt;. In addition the chance for a larger number of dictionary meanings is larger for a more frequent character (see &lt;a href=&quot;<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.g006&quot" rel="nofollow">http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.g006&quot</a>; target=&quot;_blank&quot;&gt;Fig 6&lt;/a&gt;). The inset shows how &lt; &lt;i&gt;k&lt;/i&gt; &gt; increases with &lt;i&gt;M&lt;/i&gt;.&lt;/p</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="93603213"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="93603213"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 93603213; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=93603213]").text(description); $(".js-view-count[data-work-id=93603213]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 93603213; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='93603213']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 93603213, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=93603213]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":93603213,"title":"Consistency test of the multiple meaning model","translated_title":"","metadata":{"abstract":"\u0026lt;p\u0026gt;According to the multiple meaning model the parameter \u0026lt;i\u0026gt;d\u0026lt;/i\u0026gt; (see \u0026lt;a href=\u0026quot;http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.t002\u0026quot; target=\u0026quot;_blank\u0026quot;\u0026gt;Table 2\u0026lt;/a\u0026gt;) should give a sensible approximative estimate of the average number of multiple meanings per character within a text \u0026lt; \u0026lt;i\u0026gt;f\u0026lt;/i\u0026gt; \u0026gt;. The figure shows that \u0026lt; \u0026lt;i\u0026gt;f\u0026lt;/i\u0026gt; \u0026gt; increases with the size of the text \u0026lt;i\u0026gt;M\u0026lt;/i\u0026gt;. This is consistent with the fact the number of uses of a character increases and hence the chance that more of its multiples meanings appears in the text. For the same reason \u0026lt; \u0026lt;i\u0026gt;f\u0026lt;/i\u0026gt; \u0026gt; increases with the average number of uses of a character \u0026lt; \u0026lt;i\u0026gt;k\u0026lt;/i\u0026gt; \u0026gt;. In addition the chance for a larger number of dictionary meanings is larger for a more frequent character (see \u0026lt;a href=\u0026quot;http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.g006\u0026quot; target=\u0026quot;_blank\u0026quot;\u0026gt;Fig 6\u0026lt;/a\u0026gt;). The inset shows how \u0026lt; \u0026lt;i\u0026gt;k\u0026lt;/i\u0026gt; \u0026gt; increases with \u0026lt;i\u0026gt;M\u0026lt;/i\u0026gt;.\u0026lt;/p","publication_date":{"day":8,"month":5,"year":2015,"errors":{}}},"translated_abstract":"\u0026lt;p\u0026gt;According to the multiple meaning model the parameter \u0026lt;i\u0026gt;d\u0026lt;/i\u0026gt; (see \u0026lt;a href=\u0026quot;http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.t002\u0026quot; target=\u0026quot;_blank\u0026quot;\u0026gt;Table 2\u0026lt;/a\u0026gt;) should give a sensible approximative estimate of the average number of multiple meanings per character within a text \u0026lt; \u0026lt;i\u0026gt;f\u0026lt;/i\u0026gt; \u0026gt;. The figure shows that \u0026lt; \u0026lt;i\u0026gt;f\u0026lt;/i\u0026gt; \u0026gt; increases with the size of the text \u0026lt;i\u0026gt;M\u0026lt;/i\u0026gt;. This is consistent with the fact the number of uses of a character increases and hence the chance that more of its multiples meanings appears in the text. For the same reason \u0026lt; \u0026lt;i\u0026gt;f\u0026lt;/i\u0026gt; \u0026gt; increases with the average number of uses of a character \u0026lt; \u0026lt;i\u0026gt;k\u0026lt;/i\u0026gt; \u0026gt;. In addition the chance for a larger number of dictionary meanings is larger for a more frequent character (see \u0026lt;a href=\u0026quot;http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.g006\u0026quot; target=\u0026quot;_blank\u0026quot;\u0026gt;Fig 6\u0026lt;/a\u0026gt;). The inset shows how \u0026lt; \u0026lt;i\u0026gt;k\u0026lt;/i\u0026gt; \u0026gt; increases with \u0026lt;i\u0026gt;M\u0026lt;/i\u0026gt;.\u0026lt;/p","internal_url":"https://www.academia.edu/93603213/Consistency_test_of_the_multiple_meaning_model","translated_internal_url":"","created_at":"2022-12-24T07:11:26.049-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":35870771,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Consistency_test_of_the_multiple_meaning_model","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":35870771,"first_name":"Petter","middle_initials":null,"last_name":"Minnhagen","page_name":"PetterMinnhagen","domain_name":"umu","created_at":"2015-10-08T06:30:55.611-07:00","display_name":"Petter Minnhagen","url":"https://umu.academia.edu/PetterMinnhagen"},"attachments":[],"research_interests":[{"id":5541,"name":"Plant Biology","url":"https://www.academia.edu/Documents/in/Plant_Biology"},{"id":6021,"name":"Cancer","url":"https://www.academia.edu/Documents/in/Cancer"},{"id":17960,"name":"Infectious Diseases","url":"https://www.academia.edu/Documents/in/Infectious_Diseases"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":265214,"name":"Rgf","url":"https://www.academia.edu/Documents/in/Rgf"},{"id":543930,"name":"Chinese Characters","url":"https://www.academia.edu/Documents/in/Chinese_Characters"},{"id":1037447,"name":"Deviation","url":"https://www.academia.edu/Documents/in/Deviation"}],"urls":[{"id":27386563,"url":"https://figshare.com/articles/Consistency_test_of_the_multiple_meaning_model_/2669068"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="93603212"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/93603212/Test_of_RGF_including_multiple_meaning_constraints"><img alt="Research paper thumbnail of Test of RGF including multiple meaning constraints" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/93603212/Test_of_RGF_including_multiple_meaning_constraints">Test of RGF including multiple meaning constraints</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">&lt;p&gt;The RGF is in each case predicted from the quadruple of state variables (&lt;i&gt;M&lt;/...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">&lt;p&gt;The RGF is in each case predicted from the quadruple of state variables (&lt;i&gt;M&lt;/i&gt;, &lt;i&gt;N&lt;/i&gt;, &lt;i&gt;k&lt;/i&gt;&lt;sub&gt;&lt;i&gt;max&lt;/i&gt;&lt;/sub&gt;, &lt;i&gt;S&lt;/i&gt;). The data is from three novels in Chinese (see &lt;a href=&quot;<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.t002&quot" rel="nofollow">http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.t002&quot</a>; target=&quot;_blank&quot;&gt;Table 2&lt;/a&gt;). The RGF predictions with multiple meaning constraint are given by the dashed curves. The RGF &lt;i&gt;without&lt;/i&gt; the multiple meaning constraint is predicted from the state variable triple (&lt;i&gt;M&lt;/i&gt;, &lt;i&gt;N&lt;/i&gt;, &lt;i&gt;k&lt;/i&gt;&lt;sub&gt;&lt;i&gt;max&lt;/i&gt;&lt;/sub&gt;) and corresponds to the dotted curves. Only when the multiple meaning constraint significantly improves the RGF-prediction can some specific interpretation be associated with it. As seen from the figure the significance increases with increasing length of the novel.&lt;/p</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="93603212"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="93603212"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 93603212; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=93603212]").text(description); $(".js-view-count[data-work-id=93603212]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 93603212; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='93603212']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 93603212, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=93603212]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":93603212,"title":"Test of RGF including multiple meaning constraints","translated_title":"","metadata":{"abstract":"\u0026lt;p\u0026gt;The RGF is in each case predicted from the quadruple of state variables (\u0026lt;i\u0026gt;M\u0026lt;/i\u0026gt;, \u0026lt;i\u0026gt;N\u0026lt;/i\u0026gt;, \u0026lt;i\u0026gt;k\u0026lt;/i\u0026gt;\u0026lt;sub\u0026gt;\u0026lt;i\u0026gt;max\u0026lt;/i\u0026gt;\u0026lt;/sub\u0026gt;, \u0026lt;i\u0026gt;S\u0026lt;/i\u0026gt;). The data is from three novels in Chinese (see \u0026lt;a href=\u0026quot;http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.t002\u0026quot; target=\u0026quot;_blank\u0026quot;\u0026gt;Table 2\u0026lt;/a\u0026gt;). The RGF predictions with multiple meaning constraint are given by the dashed curves. The RGF \u0026lt;i\u0026gt;without\u0026lt;/i\u0026gt; the multiple meaning constraint is predicted from the state variable triple (\u0026lt;i\u0026gt;M\u0026lt;/i\u0026gt;, \u0026lt;i\u0026gt;N\u0026lt;/i\u0026gt;, \u0026lt;i\u0026gt;k\u0026lt;/i\u0026gt;\u0026lt;sub\u0026gt;\u0026lt;i\u0026gt;max\u0026lt;/i\u0026gt;\u0026lt;/sub\u0026gt;) and corresponds to the dotted curves. Only when the multiple meaning constraint significantly improves the RGF-prediction can some specific interpretation be associated with it. As seen from the figure the significance increases with increasing length of the novel.\u0026lt;/p","publication_date":{"day":8,"month":5,"year":2015,"errors":{}}},"translated_abstract":"\u0026lt;p\u0026gt;The RGF is in each case predicted from the quadruple of state variables (\u0026lt;i\u0026gt;M\u0026lt;/i\u0026gt;, \u0026lt;i\u0026gt;N\u0026lt;/i\u0026gt;, \u0026lt;i\u0026gt;k\u0026lt;/i\u0026gt;\u0026lt;sub\u0026gt;\u0026lt;i\u0026gt;max\u0026lt;/i\u0026gt;\u0026lt;/sub\u0026gt;, \u0026lt;i\u0026gt;S\u0026lt;/i\u0026gt;). The data is from three novels in Chinese (see \u0026lt;a href=\u0026quot;http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.t002\u0026quot; target=\u0026quot;_blank\u0026quot;\u0026gt;Table 2\u0026lt;/a\u0026gt;). The RGF predictions with multiple meaning constraint are given by the dashed curves. The RGF \u0026lt;i\u0026gt;without\u0026lt;/i\u0026gt; the multiple meaning constraint is predicted from the state variable triple (\u0026lt;i\u0026gt;M\u0026lt;/i\u0026gt;, \u0026lt;i\u0026gt;N\u0026lt;/i\u0026gt;, \u0026lt;i\u0026gt;k\u0026lt;/i\u0026gt;\u0026lt;sub\u0026gt;\u0026lt;i\u0026gt;max\u0026lt;/i\u0026gt;\u0026lt;/sub\u0026gt;) and corresponds to the dotted curves. Only when the multiple meaning constraint significantly improves the RGF-prediction can some specific interpretation be associated with it. As seen from the figure the significance increases with increasing length of the novel.\u0026lt;/p","internal_url":"https://www.academia.edu/93603212/Test_of_RGF_including_multiple_meaning_constraints","translated_internal_url":"","created_at":"2022-12-24T07:11:25.889-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":35870771,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Test_of_RGF_including_multiple_meaning_constraints","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":35870771,"first_name":"Petter","middle_initials":null,"last_name":"Minnhagen","page_name":"PetterMinnhagen","domain_name":"umu","created_at":"2015-10-08T06:30:55.611-07:00","display_name":"Petter Minnhagen","url":"https://umu.academia.edu/PetterMinnhagen"},"attachments":[],"research_interests":[{"id":5541,"name":"Plant Biology","url":"https://www.academia.edu/Documents/in/Plant_Biology"},{"id":6021,"name":"Cancer","url":"https://www.academia.edu/Documents/in/Cancer"},{"id":17960,"name":"Infectious Diseases","url":"https://www.academia.edu/Documents/in/Infectious_Diseases"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":265214,"name":"Rgf","url":"https://www.academia.edu/Documents/in/Rgf"},{"id":543930,"name":"Chinese Characters","url":"https://www.academia.edu/Documents/in/Chinese_Characters"},{"id":1037447,"name":"Deviation","url":"https://www.academia.edu/Documents/in/Deviation"}],"urls":[{"id":27386562,"url":"https://figshare.com/articles/Test_of_RGF_including_multiple_meaning_constraints_/2669065"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="93603211"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/93603211/Comparison_between_Chinese_texts_in_characters_and_words"><img alt="Research paper thumbnail of Comparison between Chinese texts in characters and words" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/93603211/Comparison_between_Chinese_texts_in_characters_and_words">Comparison between Chinese texts in characters and words</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">&lt;p&gt;(a) Comparison between characters and words for the novel &lt;i&gt;A Q Zheng Zhuan&lt;/i...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">&lt;p&gt;(a) Comparison between characters and words for the novel &lt;i&gt;A Q Zheng Zhuan&lt;/i&gt; by Xun Lu together with the respective RGF-predictions. (b) The same comparison for the novel &lt;i&gt;Ping Fan De Shi Jie&lt;/i&gt; by Yao Lu. Filled dots correspond to the binned data for Chinese characters and filled triangles the data for words. Full and dashed curves correspond to the respective RGF-predictions and dotted straight lines are the Zipf’s law expectations for the word-frequency distribution. The respective “state”-variables (&lt;i&gt;M&lt;/i&gt;, &lt;i&gt;N&lt;/i&gt;, &lt;i&gt;k&lt;/i&gt;&lt;sub&gt;&lt;i&gt;max&lt;/i&gt;&lt;/sub&gt;) and the corresponding RGF-predictions are given in &lt;a href=&quot;<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.t001&quot" rel="nofollow">http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.t001&quot</a>; target=&quot;_blank&quot;&gt;Table 1&lt;/a&gt;. Note that the translation between words and characters is a deterministic process. Yet the “state”-variables (&lt;i&gt;M&lt;/i&gt;, &lt;i&gt;N&lt;/i&gt;, &lt;i&gt;k&lt;/i&gt;&lt;sub&gt;&lt;i&gt;max&lt;/i&gt;&lt;/sub&gt;) suffice to predict the change in frequency distribution caused by the translation between words and characters.&lt;/p</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="93603211"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="93603211"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 93603211; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=93603211]").text(description); $(".js-view-count[data-work-id=93603211]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 93603211; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='93603211']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 93603211, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=93603211]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":93603211,"title":"Comparison between Chinese texts in characters and words","translated_title":"","metadata":{"abstract":"\u0026lt;p\u0026gt;(a) Comparison between characters and words for the novel \u0026lt;i\u0026gt;A Q Zheng Zhuan\u0026lt;/i\u0026gt; by Xun Lu together with the respective RGF-predictions. (b) The same comparison for the novel \u0026lt;i\u0026gt;Ping Fan De Shi Jie\u0026lt;/i\u0026gt; by Yao Lu. Filled dots correspond to the binned data for Chinese characters and filled triangles the data for words. Full and dashed curves correspond to the respective RGF-predictions and dotted straight lines are the Zipf’s law expectations for the word-frequency distribution. The respective “state”-variables (\u0026lt;i\u0026gt;M\u0026lt;/i\u0026gt;, \u0026lt;i\u0026gt;N\u0026lt;/i\u0026gt;, \u0026lt;i\u0026gt;k\u0026lt;/i\u0026gt;\u0026lt;sub\u0026gt;\u0026lt;i\u0026gt;max\u0026lt;/i\u0026gt;\u0026lt;/sub\u0026gt;) and the corresponding RGF-predictions are given in \u0026lt;a href=\u0026quot;http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.t001\u0026quot; target=\u0026quot;_blank\u0026quot;\u0026gt;Table 1\u0026lt;/a\u0026gt;. Note that the translation between words and characters is a deterministic process. Yet the “state”-variables (\u0026lt;i\u0026gt;M\u0026lt;/i\u0026gt;, \u0026lt;i\u0026gt;N\u0026lt;/i\u0026gt;, \u0026lt;i\u0026gt;k\u0026lt;/i\u0026gt;\u0026lt;sub\u0026gt;\u0026lt;i\u0026gt;max\u0026lt;/i\u0026gt;\u0026lt;/sub\u0026gt;) suffice to predict the change in frequency distribution caused by the translation between words and characters.\u0026lt;/p","publication_date":{"day":8,"month":5,"year":2015,"errors":{}}},"translated_abstract":"\u0026lt;p\u0026gt;(a) Comparison between characters and words for the novel \u0026lt;i\u0026gt;A Q Zheng Zhuan\u0026lt;/i\u0026gt; by Xun Lu together with the respective RGF-predictions. (b) The same comparison for the novel \u0026lt;i\u0026gt;Ping Fan De Shi Jie\u0026lt;/i\u0026gt; by Yao Lu. Filled dots correspond to the binned data for Chinese characters and filled triangles the data for words. Full and dashed curves correspond to the respective RGF-predictions and dotted straight lines are the Zipf’s law expectations for the word-frequency distribution. The respective “state”-variables (\u0026lt;i\u0026gt;M\u0026lt;/i\u0026gt;, \u0026lt;i\u0026gt;N\u0026lt;/i\u0026gt;, \u0026lt;i\u0026gt;k\u0026lt;/i\u0026gt;\u0026lt;sub\u0026gt;\u0026lt;i\u0026gt;max\u0026lt;/i\u0026gt;\u0026lt;/sub\u0026gt;) and the corresponding RGF-predictions are given in \u0026lt;a href=\u0026quot;http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.t001\u0026quot; target=\u0026quot;_blank\u0026quot;\u0026gt;Table 1\u0026lt;/a\u0026gt;. Note that the translation between words and characters is a deterministic process. Yet the “state”-variables (\u0026lt;i\u0026gt;M\u0026lt;/i\u0026gt;, \u0026lt;i\u0026gt;N\u0026lt;/i\u0026gt;, \u0026lt;i\u0026gt;k\u0026lt;/i\u0026gt;\u0026lt;sub\u0026gt;\u0026lt;i\u0026gt;max\u0026lt;/i\u0026gt;\u0026lt;/sub\u0026gt;) suffice to predict the change in frequency distribution caused by the translation between words and characters.\u0026lt;/p","internal_url":"https://www.academia.edu/93603211/Comparison_between_Chinese_texts_in_characters_and_words","translated_internal_url":"","created_at":"2022-12-24T07:11:25.718-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":35870771,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Comparison_between_Chinese_texts_in_characters_and_words","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":35870771,"first_name":"Petter","middle_initials":null,"last_name":"Minnhagen","page_name":"PetterMinnhagen","domain_name":"umu","created_at":"2015-10-08T06:30:55.611-07:00","display_name":"Petter Minnhagen","url":"https://umu.academia.edu/PetterMinnhagen"},"attachments":[],"research_interests":[{"id":5541,"name":"Plant Biology","url":"https://www.academia.edu/Documents/in/Plant_Biology"},{"id":6021,"name":"Cancer","url":"https://www.academia.edu/Documents/in/Cancer"},{"id":17960,"name":"Infectious Diseases","url":"https://www.academia.edu/Documents/in/Infectious_Diseases"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":265214,"name":"Rgf","url":"https://www.academia.edu/Documents/in/Rgf"},{"id":543930,"name":"Chinese Characters","url":"https://www.academia.edu/Documents/in/Chinese_Characters"},{"id":1037447,"name":"Deviation","url":"https://www.academia.edu/Documents/in/Deviation"}],"urls":[{"id":27386561,"url":"https://figshare.com/articles/Comparison_between_Chinese_texts_in_characters_and_words_/2668996"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="93603210"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/93603210/Size_dependence_of_novels_written_in_Chinese_characters"><img alt="Research paper thumbnail of Size dependence of novels written in Chinese characters" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/93603210/Size_dependence_of_novels_written_in_Chinese_characters">Size dependence of novels written in Chinese characters</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">&lt;p&gt;The same two novels as in &lt;a href=&quot;http://www.plosone.org/article/info:doi/10.13...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">&lt;p&gt;The same two novels as in &lt;a href=&quot;<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.g002&quot" rel="nofollow">http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.g002&quot</a>; target=&quot;_blank&quot;&gt;Fig 2&lt;/a&gt; are divided into parts. The frequency distribution of a full novel is compared to the one of a part. (a) &lt;i&gt;P&lt;/i&gt;(&lt;i&gt;k&lt;/i&gt;) for &lt;i&gt;A Q Zheng Zhuan&lt;/i&gt; (filled dots) is compared to the distribution for a typical 10&lt;sup&gt;&lt;i&gt;th&lt;/i&gt;&lt;/sup&gt;-part (filled triangles). Here the word &lt;i&gt;typical&lt;/i&gt; means an average distribution obtained by taking many different 10&lt;sup&gt;&lt;i&gt;th&lt;/i&gt;&lt;/sup&gt; with different starting points. These two functions have quite different shapes. However, the shapes of both are equally well predicted by RGF (curves with dashed and full lines). (b) The distribution of the 10&lt;sup&gt;&lt;i&gt;th&lt;/i&gt;&lt;/sup&gt;-part, which can to very good approximation be trivially obtained from the full book by just &lt;i&gt;randomly&lt;/i&gt; removing 90% of the words from the full book. This corresponds to the dashed curve which is almost identical to the RGF-prediction and both correspond very well to the data. (c-d) The same features for the novel &lt;i&gt;Ping Fan De Shi Jie&lt;/i&gt;. Note that the 10&lt;sup&gt;&lt;i&gt;th&lt;/i&gt;&lt;/sup&gt;-part agrees better with RGF than the full novel.&lt;/p</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="93603210"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="93603210"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 93603210; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=93603210]").text(description); $(".js-view-count[data-work-id=93603210]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 93603210; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='93603210']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 93603210, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=93603210]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":93603210,"title":"Size dependence of novels written in Chinese characters","translated_title":"","metadata":{"abstract":"\u0026lt;p\u0026gt;The same two novels as in \u0026lt;a href=\u0026quot;http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.g002\u0026quot; target=\u0026quot;_blank\u0026quot;\u0026gt;Fig 2\u0026lt;/a\u0026gt; are divided into parts. The frequency distribution of a full novel is compared to the one of a part. (a) \u0026lt;i\u0026gt;P\u0026lt;/i\u0026gt;(\u0026lt;i\u0026gt;k\u0026lt;/i\u0026gt;) for \u0026lt;i\u0026gt;A Q Zheng Zhuan\u0026lt;/i\u0026gt; (filled dots) is compared to the distribution for a typical 10\u0026lt;sup\u0026gt;\u0026lt;i\u0026gt;th\u0026lt;/i\u0026gt;\u0026lt;/sup\u0026gt;-part (filled triangles). Here the word \u0026lt;i\u0026gt;typical\u0026lt;/i\u0026gt; means an average distribution obtained by taking many different 10\u0026lt;sup\u0026gt;\u0026lt;i\u0026gt;th\u0026lt;/i\u0026gt;\u0026lt;/sup\u0026gt; with different starting points. These two functions have quite different shapes. However, the shapes of both are equally well predicted by RGF (curves with dashed and full lines). (b) The distribution of the 10\u0026lt;sup\u0026gt;\u0026lt;i\u0026gt;th\u0026lt;/i\u0026gt;\u0026lt;/sup\u0026gt;-part, which can to very good approximation be trivially obtained from the full book by just \u0026lt;i\u0026gt;randomly\u0026lt;/i\u0026gt; removing 90% of the words from the full book. This corresponds to the dashed curve which is almost identical to the RGF-prediction and both correspond very well to the data. (c-d) The same features for the novel \u0026lt;i\u0026gt;Ping Fan De Shi Jie\u0026lt;/i\u0026gt;. Note that the 10\u0026lt;sup\u0026gt;\u0026lt;i\u0026gt;th\u0026lt;/i\u0026gt;\u0026lt;/sup\u0026gt;-part agrees better with RGF than the full novel.\u0026lt;/p","publication_date":{"day":8,"month":5,"year":2015,"errors":{}}},"translated_abstract":"\u0026lt;p\u0026gt;The same two novels as in \u0026lt;a href=\u0026quot;http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125592#pone.0125592.g002\u0026quot; target=\u0026quot;_blank\u0026quot;\u0026gt;Fig 2\u0026lt;/a\u0026gt; are divided into parts. The frequency distribution of a full novel is compared to the one of a part. (a) \u0026lt;i\u0026gt;P\u0026lt;/i\u0026gt;(\u0026lt;i\u0026gt;k\u0026lt;/i\u0026gt;) for \u0026lt;i\u0026gt;A Q Zheng Zhuan\u0026lt;/i\u0026gt; (filled dots) is compared to the distribution for a typical 10\u0026lt;sup\u0026gt;\u0026lt;i\u0026gt;th\u0026lt;/i\u0026gt;\u0026lt;/sup\u0026gt;-part (filled triangles). Here the word \u0026lt;i\u0026gt;typical\u0026lt;/i\u0026gt; means an average distribution obtained by taking many different 10\u0026lt;sup\u0026gt;\u0026lt;i\u0026gt;th\u0026lt;/i\u0026gt;\u0026lt;/sup\u0026gt; with different starting points. These two functions have quite different shapes. However, the shapes of both are equally well predicted by RGF (curves with dashed and full lines). (b) The distribution of the 10\u0026lt;sup\u0026gt;\u0026lt;i\u0026gt;th\u0026lt;/i\u0026gt;\u0026lt;/sup\u0026gt;-part, which can to very good approximation be trivially obtained from the full book by just \u0026lt;i\u0026gt;randomly\u0026lt;/i\u0026gt; removing 90% of the words from the full book. This corresponds to the dashed curve which is almost identical to the RGF-prediction and both correspond very well to the data. (c-d) The same features for the novel \u0026lt;i\u0026gt;Ping Fan De Shi Jie\u0026lt;/i\u0026gt;. Note that the 10\u0026lt;sup\u0026gt;\u0026lt;i\u0026gt;th\u0026lt;/i\u0026gt;\u0026lt;/sup\u0026gt;-part agrees better with RGF than the full novel.\u0026lt;/p","internal_url":"https://www.academia.edu/93603210/Size_dependence_of_novels_written_in_Chinese_characters","translated_internal_url":"","created_at":"2022-12-24T07:11:25.536-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":35870771,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Size_dependence_of_novels_written_in_Chinese_characters","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":35870771,"first_name":"Petter","middle_initials":null,"last_name":"Minnhagen","page_name":"PetterMinnhagen","domain_name":"umu","created_at":"2015-10-08T06:30:55.611-07:00","display_name":"Petter Minnhagen","url":"https://umu.academia.edu/PetterMinnhagen"},"attachments":[],"research_interests":[{"id":5541,"name":"Plant Biology","url":"https://www.academia.edu/Documents/in/Plant_Biology"},{"id":6021,"name":"Cancer","url":"https://www.academia.edu/Documents/in/Cancer"},{"id":17960,"name":"Infectious Diseases","url":"https://www.academia.edu/Documents/in/Infectious_Diseases"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":265214,"name":"Rgf","url":"https://www.academia.edu/Documents/in/Rgf"},{"id":543930,"name":"Chinese Characters","url":"https://www.academia.edu/Documents/in/Chinese_Characters"},{"id":1037447,"name":"Deviation","url":"https://www.academia.edu/Documents/in/Deviation"}],"urls":[{"id":27386560,"url":"https://figshare.com/articles/Size_dependence_of_novels_written_in_Chinese_characters_/2669032"}]}, dispatcherData: dispatcherData }); 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Within this new description, the prediction of a universal jump or the prediction that the exponent q is 4 at the critical line breaks down below a certain temperature. Consequently it should be possible to have a Kosterlitz-Thouless transition without a universal jump. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="93603154"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/93603154/New_renormalization_equations_for_the_Kosterlitz_Thouless_transition"><img alt="Research paper thumbnail of New renormalization equations for the Kosterlitz-Thouless transition" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/93603154/New_renormalization_equations_for_the_Kosterlitz_Thouless_transition">New renormalization equations for the Kosterlitz-Thouless transition</a></div><div class="wp-workCard_item"><span>Physical Review B</span><span>, 1985</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">A new set of renormalization equations for the two-dimensional Coulomb gas is derived and solved ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">A new set of renormalization equations for the two-dimensional Coulomb gas is derived and solved numerically. These equations give a new picture of the Kosterlitz-Thouless transition. A new temperature T* is found. Above T* the value of the dielectric constant at the transition is εc=1/(4Tc) as before whereas below T* the new result εc&amp;amp;amp;amp;amp;amp;lt;1/(4Tc) is obtained. The singular behavior at</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="93603154"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="93603154"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 93603154; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=93603154]").text(description); $(".js-view-count[data-work-id=93603154]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 93603154; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='93603154']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 93603154, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=93603154]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":93603154,"title":"New renormalization equations for the Kosterlitz-Thouless transition","translated_title":"","metadata":{"abstract":"A new set of renormalization equations for the two-dimensional Coulomb gas is derived and solved numerically. These equations give a new picture of the Kosterlitz-Thouless transition. A new temperature T* is found. Above T* the value of the dielectric constant at the transition is εc=1/(4Tc) as before whereas below T* the new result εc\u0026amp;amp;amp;amp;amp;amp;lt;1/(4Tc) is obtained. The singular behavior at","publisher":"American Physical Society (APS)","publication_date":{"day":null,"month":null,"year":1985,"errors":{}},"publication_name":"Physical Review B"},"translated_abstract":"A new set of renormalization equations for the two-dimensional Coulomb gas is derived and solved numerically. These equations give a new picture of the Kosterlitz-Thouless transition. A new temperature T* is found. Above T* the value of the dielectric constant at the transition is εc=1/(4Tc) as before whereas below T* the new result εc\u0026amp;amp;amp;amp;amp;amp;lt;1/(4Tc) is obtained. The singular behavior at","internal_url":"https://www.academia.edu/93603154/New_renormalization_equations_for_the_Kosterlitz_Thouless_transition","translated_internal_url":"","created_at":"2022-12-24T07:09:27.159-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":35870771,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"New_renormalization_equations_for_the_Kosterlitz_Thouless_transition","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":35870771,"first_name":"Petter","middle_initials":null,"last_name":"Minnhagen","page_name":"PetterMinnhagen","domain_name":"umu","created_at":"2015-10-08T06:30:55.611-07:00","display_name":"Petter Minnhagen","url":"https://umu.academia.edu/PetterMinnhagen"},"attachments":[],"research_interests":[{"id":318,"name":"Mathematical Physics","url":"https://www.academia.edu/Documents/in/Mathematical_Physics"},{"id":498,"name":"Physics","url":"https://www.academia.edu/Documents/in/Physics"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":192257,"name":"Physical","url":"https://www.academia.edu/Documents/in/Physical"},{"id":201464,"name":"Renormalization","url":"https://www.academia.edu/Documents/in/Renormalization"},{"id":288867,"name":"Coulomb","url":"https://www.academia.edu/Documents/in/Coulomb"},{"id":389578,"name":"Dielectric Constant","url":"https://www.academia.edu/Documents/in/Dielectric_Constant"},{"id":434746,"name":"Model System","url":"https://www.academia.edu/Documents/in/Model_System"},{"id":494966,"name":"Renormalization Group","url":"https://www.academia.edu/Documents/in/Renormalization_Group"},{"id":1130298,"name":"Critical Point","url":"https://www.academia.edu/Documents/in/Critical_Point"},{"id":1394433,"name":"Critical Temperature","url":"https://www.academia.edu/Documents/in/Critical_Temperature"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="88930895"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/88930895/The_two_dimensional_Coulomb_gas_vortex_unbinding_and_superfluid_superconducting_films"><img alt="Research paper thumbnail of The two-dimensional Coulomb gas, vortex unbinding, and superfluid-superconducting films" class="work-thumbnail" src="https://attachments.academia-assets.com/92819037/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/88930895/The_two_dimensional_Coulomb_gas_vortex_unbinding_and_superfluid_superconducting_films">The two-dimensional Coulomb gas, vortex unbinding, and superfluid-superconducting films</a></div><div class="wp-workCard_item"><span>Reviews of Modern Physics</span><span>, 1987</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="b5519d9eccc713d81a0f559c24a0a12c" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":92819037,"asset_id":88930895,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/92819037/download_file?st=MTczMzAxNzgxOCw4LjIyMi4yMDguMTQ2&st=MTczMzAxNzgxNyw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="88930895"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="88930895"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 88930895; 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dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "b5519d9eccc713d81a0f559c24a0a12c" } } $('.js-work-strip[data-work-id=88930895]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":88930895,"title":"The two-dimensional Coulomb gas, vortex unbinding, and superfluid-superconducting films","translated_title":"","metadata":{"publisher":"American Physical Society (APS)","grobid_abstract":"The article reviews the two-dimensional Coulomb gas model and its connection to vortex fluctuations for a two-dimensional superfluid. The neutral and non-neutral versions of the Coulomb gas are discussed and the relation to an equivalent sine-Gordon field theory is given. The charge-unbinding picture is used to elucidate some essential properties of the Coulomb gas. Derivations of approximate renormalization equations are sketched and the phase transition for the neutral two-dimensional Coulomb gas is described. The Kosterlitz renormalization-group equations are reviewed in some detail. The vortex-Coulomb gas charge analogy is carefully explained. The connections between experiments for 4He films and superconducting films and the neutral and non-neutral versions of the Coulomb gas are outlined using concepts like the universal jurnp and the Coulomb gas scaling relations. The properties of a dynamical version of the Coulomb gas, corresponding to vortex dynamics, are discussed and related to experiments. An analogy with Maxwell's equations in two dimensions is also given.","publication_date":{"day":null,"month":null,"year":1987,"errors":{}},"publication_name":"Reviews of Modern 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="75678809"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/75678809/Exact_numerical_solutions_of_a_nozieres_de_dominicis_type_model_problem"><img alt="Research paper thumbnail of Exact numerical solutions of a nozieres-de dominicis-type model problem" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/75678809/Exact_numerical_solutions_of_a_nozieres_de_dominicis_type_model_problem">Exact numerical solutions of a nozieres-de dominicis-type model problem</a></div><div class="wp-workCard_item"><span>Physics Letters A</span><span>, 1976</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">We infer from a model calculation that, to a very good approximation, the XPS spectra from core e...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">We infer from a model calculation that, to a very good approximation, the XPS spectra from core electrons in simple metals should follow the edge power law up to the first plasmon satellite. The power law indices obtained are in good agreement with recent experimental XPS values for Na, Mg and Al.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="75678809"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75678809"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75678809; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75678809]").text(description); $(".js-view-count[data-work-id=75678809]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75678809; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75678809']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 75678809, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=75678809]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75678809,"title":"Exact numerical solutions of a nozieres-de dominicis-type model problem","translated_title":"","metadata":{"abstract":"We infer from a model calculation that, to a very good approximation, the XPS spectra from core electrons in simple metals should follow the edge power law up to the first plasmon satellite. 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We investigate the phase diagram in the plane of the temperature T and the disorder strength r, and infer, in contrast to a prevailing conclusion in many earlier studies, that the system is superconducting at any disorder strength r for sufficiently low T. It is also argued that the superconducting to normal transition has different nature at weak disorder and strong disorder: termed Kosterlitz-Thouless (KT) type and non-KT type, respectively. The results are compared to earlier works.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="54a26c453852e2aa17e3feea2627827c" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":81279599,"asset_id":72296061,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/81279599/download_file?st=MTczMzAxNzgxOCw4LjIyMi4yMDguMTQ2&st=MTczMzAxNzgxOCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="72296061"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="72296061"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 72296061; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=72296061]").text(description); $(".js-view-count[data-work-id=72296061]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 72296061; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='72296061']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 72296061, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "54a26c453852e2aa17e3feea2627827c" } } $('.js-work-strip[data-work-id=72296061]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":72296061,"title":"Phase Transitions in the Two-Dimensional Random Gauge XY Model","translated_title":"","metadata":{"abstract":"The two-dimensional random gauge model, where the quenched random variables are magnetic bond angles uniformly distributed within [-rπ, rπ] (0 ≤ r ≤ 1), is studied via Monte Carlo simulations. 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